Mastodawn

AI Transforms Scientific Discovery: How AlphaFold and AI Co-Scientist Are Reshaping Research

https://techlife.blog/posts/ai-transforms-scientific-discovery-alphafold-ai-co-scientist/

#AlphaFold #Google #DeepMind #ScientificDiscovery #ProteinStructure #Gemini #NobelPrize #AIResearch #AlphaEvolve #BioNeMo #AI

AI Transforms Scientific Discovery: How AlphaFold and AI Co-Scientist Are Reshaping Research

From solving the 50-year protein folding problem to generating research hypotheses in hours, AI tools like AlphaFold and Google's AI Co-Scientist are compressing discovery timelines from years to days

TechLife

InfoQ Dec 18

#GoogleCloud announced the private preview of #AlphaEvolve!

A Gemini-powered coding agent, AlphaEvolve is designed to discover & optimize algorithms for complex engineering and scientific challenges - especially where brute-force or manual approaches break down due to massive search spaces.

👉 Learn more: https://bit.ly/48LxdJi

#InfoQ #AI #LLMs #Gemini

Alessio Pomaro Dec 10

🧠 In diverse occasioni mi è capitato di parlare del progetto #AlphaEvolve di #Google… e ora sta arrivando su Google Cloud.
👉 I dettagli: https://www.linkedin.com/posts/alessiopomaro_alphaevolve-google-gemini-activity-7404492798437068801-Ncgv

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✉️ 𝗦𝗲 𝘃𝘂𝗼𝗶 𝗿𝗶𝗺𝗮𝗻𝗲𝗿𝗲 𝗮𝗴𝗴𝗶𝗼𝗿𝗻𝗮𝘁𝗼/𝗮 𝘀𝘂 𝗾𝘂𝗲𝘀𝘁𝗲 𝘁𝗲𝗺𝗮𝘁𝗶𝗰𝗵𝗲, 𝗶𝘀𝗰𝗿𝗶𝘃𝗶𝘁𝗶 𝗮𝗹𝗹𝗮 𝗺𝗶𝗮 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿: https://bit.ly/newsletter-alessiopomaro

#AI #GenAI #GenerativeAI #IntelligenzaArtificiale #LLM

José A. Alonso Dec 9

The story of Erdős problem #1026. ~ Terence Tao. https://terrytao.wordpress.com/2025/12/08/the-story-of-erdos-problem-126/ #AI #Math #ITP #LeanProver #Aristotle #AlphaEvolve

The story of Erdős problem #126

Problem 1026 on the Erdős problem web site recently got solved through an interesting combination of existing literature, online collaboration, and AI tools. The purpose of this blog post is to try…

What's new

AI Sparkup Nov 11

필즈상 수상자가 AI로 수학 문제 67개 풀어본 결과: 300년 난제도 개선

필즈상 수상자 테렌스 타오가 AI 도구 AlphaEvolve로 67개 수학 문제를 테스트한 결과. 75% 재발견, 20% 개선, 300년 묵은 키싱 넘버 문제도 돌파했습니다.

https://aisparkup.com/posts/6365

José A. Alonso Nov 8

Readings shared November 7, 2025. https://jaalonso.github.io/vestigium/posts/2025/11/08-readings_shared_11-07-25 #AI #Agda #AlphaEvolve #FormalVerification #FunctionalProgramming #Haskell #HoTT #ITP #LLM #LeanProver #Math #Rocq

Readings shared November 7, 2025

The readings shared in Bluesky on 7 November 2025 are: An introduction to formal real analysis (Lecture 16: Completeness of the real numbers). ~ Alex Kontorovich. #ITP #LeanProver #Math The path to a

Vestigium

Winbuzzer Nov 7

Google DeepMind and Fields Medalist Terence Tao Detail AI-Powered Mathematical Discoveries with AlphaEvolve

#AI #GoogleDeepMind #Mathematics #AlphaEvolve #TerenceTao #Science #Research #MachineLearning #Google #AIinScience #DeepLearning #ComputerScience

https://winbuzzer.com/2025/11/07/google-deepmind-and-fields-medalist-terence-tao-detail-ai-powered-mathematical-discoveries-with-alphaevolve-xcxwbn

José A. Alonso Nov 7

Mathematical exploration and discovery at scale. ~ Bogdan Georgiev, Javier Gómez-Serrano, Terence Tao, Adam Zsolt Wagner. https://arxiv.org/abs/2511.02864v1 #AI #Math #AlphaEvolve #ITP #LeanProver

Mathematical exploration and discovery at scale

AlphaEvolve is a generic evolutionary coding agent that combines the generative capabilities of LLMs with automated evaluation in an iterative evolutionary framework that proposes, tests, and refines algorithmic solutions to challenging scientific and practical problems. In this paper we showcase AlphaEvolve as a tool for autonomously discovering novel mathematical constructions and advancing our understanding of long-standing open problems. To demonstrate its breadth, we considered a list of 67 problems spanning mathematical analysis, combinatorics, geometry, and number theory. The system rediscovered the best known solutions in most of the cases and discovered improved solutions in several. In some instances, AlphaEvolve is also able to generalize results for a finite number of input values into a formula valid for all input values. Furthermore, we are able to combine this methodology with Deep Think and AlphaProof in a broader framework where the additional proof-assistants and reasoning systems provide automated proof generation and further mathematical insights. These results demonstrate that large language model-guided evolutionary search can autonomously discover mathematical constructions that complement human intuition, at times matching or even improving the best known results, highlighting the potential for significant new ways of interaction between mathematicians and AI systems. We present AlphaEvolve as a powerful new tool for mathematical discovery, capable of exploring vast search spaces to solve complex optimization problems at scale, often with significantly reduced requirements on preparation and computation time.

arXiv.org

Terence Tao Nov 6

A new paper with Bogdan Georgiev, Javier Gomez-Serrano, and Adam Zsolt Wagner: "Mathematical exploration and discovery at scale" https://arxiv.org/abs/2511.02864 , in which we record our experiments using the LLM-powered optimization tool #AlphaEvolve to attack 67 different math problems (both solved and unsolved), improving upon the state of the art in some cases and matching preivous literature in others. The data for these experiments can be found at https://github.com/google-deepmind/alphaevolve_repository_of_problems and further discussion is at https://terrytao.wordpress.com/2025/11/05/mathematical-exploration-and-discovery-at-scale/

Mathematical exploration and discovery at scale

AlphaEvolve is a generic evolutionary coding agent that combines the generative capabilities of LLMs with automated evaluation in an iterative evolutionary framework that proposes, tests, and refines algorithmic solutions to challenging scientific and practical problems. In this paper we showcase AlphaEvolve as a tool for autonomously discovering novel mathematical constructions and advancing our understanding of long-standing open problems. To demonstrate its breadth, we considered a list of 67 problems spanning mathematical analysis, combinatorics, geometry, and number theory. The system rediscovered the best known solutions in most of the cases and discovered improved solutions in several. In some instances, AlphaEvolve is also able to generalize results for a finite number of input values into a formula valid for all input values. Furthermore, we are able to combine this methodology with Deep Think and AlphaProof in a broader framework where the additional proof-assistants and reasoning systems provide automated proof generation and further mathematical insights. These results demonstrate that large language model-guided evolutionary search can autonomously discover mathematical constructions that complement human intuition, at times matching or even improving the best known results, highlighting the potential for significant new ways of interaction between mathematicians and AI systems. We present AlphaEvolve as a powerful new tool for mathematical discovery, capable of exploring vast search spaces to solve complex optimization problems at scale, often with significantly reduced requirements on preparation and computation time.

arXiv.org

N_E_O Jul 28, 2025

Here is a Podcast about #AlphaEvolve if you like listening to it:

https://open.spotify.com/episode/27NyNebqx3BjYjGbgNX46D?si

Google AlphaEvolve - Discovering new science (exclusive interview)

Spotify